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How fast a state of a system converges to a stationary state is one of the fundamental questions in science. Some Markov chains and random walks on finite groups are known to exhibit the non-asymptotic convergence to a stationary…

Quantum Physics · Physics 2024-02-01 Sangchul Oh , Sabre Kais

We obtain quenched hitting distributions to be compound Poissonian for a certain class of random dynamical systems. The theory is general and designed to accommodate non-uniformly expanding behavior and targets that do not overlap much with…

Dynamical Systems · Mathematics 2024-02-06 Lucas Amorim , Nicolai Haydn , Sandro Vaienti

In this article we investigate the asymptotic behavior of a new class of multi-dimensional diffusions in random environment. We introduce cut times in the spirit of the work done by Bolthausen, Sznitman and Zeitouni, see [4], in the…

Probability · Mathematics 2009-12-12 Ivan del Tenno

We study a coarsening model describing the dynamics of interfaces in the one-dimensional Allen-Cahn equation. Given a partition of the real line into intervals of length greater than one, the model consists in constantly eliminating the…

Analysis of PDEs · Mathematics 2007-05-23 Th. Gallay , A. Mielke

We study the kinetic mean field Langevin dynamics under the functional convexity assumption of the mean field energy functional. Using hypocoercivity, we first establish the exponential convergence of the mean field dynamics and then show…

Probability · Mathematics 2024-02-09 Fan Chen , Yiqing Lin , Zhenjie Ren , Songbo Wang

We study a nonlinear recombination model from population genetics as a combinatorial version of the Kac-Boltzmann equation from kinetic theory. Following Kac's approach, the nonlinear model is approximated by a mean field linear evolution…

Probability · Mathematics 2024-12-24 Pietro Caputo , Daniel Parisi

In this paper, we investigate gradient estimate of the Poisson equation and the exponential convergence in the Wasserstein metric $W_{1,d_{l^1}}$, uniform in the number of particles, and uniform-in-time propagation of chaos for the…

Probability · Mathematics 2021-09-15 Wei Liu , Liming Wu , Chaoen Zhang

A natural generalization of interval exchange maps are linear involutions, first introduced by Danthony and Nogueira. Recurrent train tracks with a single switch provide a subclass of linear involutions. We call such linear involutions…

Dynamical Systems · Mathematics 2011-08-04 Vaibhav S Gadre

We develop a quantitative statistical theory of transformers in the large-context regime by adopting the abstraction of contextual flow maps (CFMs): dynamical systems that evolve a distinguished token in the presence of a contextual measure…

Machine Learning · Computer Science 2026-05-19 Shi Chen , Zhengjiang Lin , Kaizhao Liu , Philippe Rigollet

We develop a mean-field theory for large, non-exchangeable particle (agent) systems where the states and interaction weights co-evolve in a coupled system of SDEs. A first main result is the establishment of the propagation of…

Probability · Mathematics 2025-12-30 Datong Zhou

The cutoff phenomenon describes a sharp transition in the convergence of an ergodic finite Markov chain to equilibrium. Of particular interest is understanding this convergence for the simple random walk on a bounded-degree expander graph.…

Probability · Mathematics 2010-03-19 Eyal Lubetzky , Allan Sly

In this paper, we are interested in the mixing behaviour of simple random walks on inhomogeneous directed graphs. We focus our study on the Chung-Lu digraph, which is an inhomogeneous network that generalizes the Erd\H{o}s-R\'enyi digraph.…

Probability · Mathematics 2024-09-25 Alessandra Bianchi , Giacomo Passuello

Michor and Mumford showed that the mean curvature flow is a gradient flow on a Riemannian structure with a degenerate geodesic distance. It is also known to destroy the uniform density of gridpoints on the evolving surfaces. We introduce a…

Analysis of PDEs · Mathematics 2018-09-18 Wenhui Shi , Dmitry Vorotnikov

The spectral properties of interacting strongly chaotic systems are investigated for growing interaction strength. A very sensitive transition from Poisson statistics to that of random matrix theory is found. We introduce a new random…

We consider the East model in $\mathbb Z^d$, an example of a kinetically constrained interacting particle system with oriented constraints, together with one of its natural variant. Under any ergodic boundary condition it is known that the…

Probability · Mathematics 2025-09-15 Concetta Campailla , Fabio Martinelli

In the present paper, we consider a class of Markov processes on the discrete circle which has been introduced by K\"onig, O'Connell and Roch. These processes describe movements of exchangeable interacting particles and are discrete…

Probability · Mathematics 2026-01-01 Anna Ben-Hamou , Pierre Tarrago

In this article we show, in a concise manner, a result of uniform in time propagation of chaos for non exchangeable systems of particles interacting according to a random graph. Provided the interaction is Lipschitz continuous, the…

Probability · Mathematics 2023-04-18 Pierre Le Bris , Christophe Poquet

A finite ergodic Markov chain exhibits cutoff if its distance to equilibrium remains close to its initial value over a certain number of iterations and then abruptly drops to near 0 on a much shorter time scale. Originally discovered in the…

Probability · Mathematics 2018-01-23 Charles Bordenave , Pietro Caputo , Justin Salez

This article establishes cutoff convergence or abrupt convergence of three statistical quantities for multivariate (Hurwitz) stable geometric Brownian motion: the autocorrelation function, the Wasserstein distance between the current state…

Probability · Mathematics 2025-06-30 G. Barrera , M. A. Högele , J. C. Pardo

We consider the biased card shuffling and the Asymmetric Simple Exclusion Process (ASEP) on the segment. We obtain the asymptotic of their mixing times: our result show that these two continuous-time Markov chains display cutoff. Our…

Probability · Mathematics 2019-05-09 Cyril Labbé , Hubert Lacoin